Yearly Traffic Safety Analysis

1,360 CRASHES IN
MEDFORD, MA
2024

All metrics benchmarked against2023

In 2024, Medford recorded 1,360 vehicle crashes, a 6.5% decrease from the 1,454 crashes reported in 2023. Despite the overall reduction in collisions, the number of people injured rose by 5.9%, from 323 to 342, while fatalities remained unchanged at one. The most notable shift in contributing factors was a 94.4% increase in the count of crashes attributed to 'Driving too fast for conditions,' which grew from 18 to 35 incidents.

1,360

-6.5%was 1,454

Total Crash Events

1

Persons Killed

342

5.9%was 323

Persons Injured

237

-9.2%was 261

Hit-and-Run Crashes

Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 135 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend in vehicle crashes in Medford shows a decline between 2023 and 2024, with total incidents falling by 6.5% from 1,454 to 1,360. In contrast to the drop in total crashes, the number of people injured increased by 5.9% from 323 to 342. The number of fatalities remained stable, with one death recorded in each year.

237

Hit-and-Run Crashes — 2024

-9.2% vs prior (261)

The number of hit-and-run crashes in Medford decreased by 9.2%, from 261 incidents in 2023 to 237 in 2024. This decline was proportional to the overall drop in crashes, resulting in a slight downward trend for the hit-and-run rate, which fell from 18.0% of all crashes in 2023 to 17.4% in 2024.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

1

Motorists Killed

Prior: 10.0%

0

Other Killed

Prior: 00.0%

24

Pedestrians Injured

Prior: 27-11.1%

17

Cyclists Injured

Prior: 21-19.0%

296

Motorists Injured

Prior: 2728.8%

5

Other Injured

Prior: 366.7%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes remained relatively consistent, with Friday being the peak day for crashes in both 2024 (222 crashes) and 2023 (235 crashes). However, the peak hour for collisions shifted earlier in the day. In 2024, the peak was the 2 p.m. hour with 113 crashes, a change from the 5 p.m. peak hour in 2023 which saw 117 crashes.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The number of fatal crashes and resulting fatalities was unchanged, with one fatal incident and one death recorded in both 2024 and 2023. The proportion of crashes resulting in any type of injury (serious, minor, or possible) increased from 18.3% in 2023 to 19.3% in 2024. This was driven by a rise in serious injury crashes (from 15 to 17) and minor injury crashes (from 167 to 181).

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.1%
0.0%prior 1
Serious Injury17serious injury crashes1.3%
13.3%prior 15
Minor Injury181minor injury crashes13.3%
8.4%prior 167
Possible Injury64possible injury crashes4.7%
-23.8%prior 84
No Injury962no injury crashes70.7%
-8.9%prior 1,056

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record

Top Contributing Factors

The top three contributing factors remained the same in both periods, though their counts decreased in line with the overall trend. A notable exception was speeding-related behavior; crashes attributed to 'Driving too fast for conditions' increased by 94.4% in count, from 18 incidents in 2023 to 35 in 2024. Similarly, crashes involving 'Exceeded authorized speed limit' rose from 14 to 17.

Officer-Reported Primary Contributing Cause

No improper driving359 (26.4%)-12.7%prior 411
Followed too closely150 (11%)-4.5%prior 157
Failed to yield right of way129 (9.5%)-5.8%prior 137
Inattention92 (6.8%)5.7%prior 87
Other improper action55 (4%)-3.5%prior 57
Failure to keep in proper lane or running off road42 (3.1%)-30.0%prior 60
Disregarded traffic signs, signals, road markings37 (2.7%)-9.8%prior 41
Driving too fast for conditions35 (2.6%)94.4%prior 18
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner32 (2.4%)6.7%prior 30
Distracted30 (2.2%)42.9%prior 21

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes in both periods predominantly occurred during daylight hours (935 in 2024 vs. 968 in 2023) and on dry roads (1,058 in 2024 vs. 1,123 in 2023). There was no significant shift in the proportion of crashes occurring under adverse conditions. Incidents during rain decreased from 132 to 102, and crashes on wet roads fell from 263 to 223, reflecting the overall reduction in total crashes.

Weather

Clear858 (64.7%)
-5.6%prior 909
Cloudy119 (9.0%)
-13.8%prior 138
Clear/Clear106 (8.0%)
24.7%prior 85
Rain102 (7.7%)
-22.7%prior 132
Cloudy/Rain21 (1.6%)
-38.2%prior 34
Rain/Cloudy16 (1.2%)
60.0%prior 10
Snow15 (1.1%)
7.1%prior 14
Unknown/Unknown11 (0.8%)
-15.4%prior 13
Sleet, hail (freezing rain or drizzle)10 (0.8%)
66.7%prior 6
Clear/Unknown10 (0.8%)
42.9%prior 7

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash

Lighting

Daylight935 (71.0%)
-3.4%prior 968
Dark - lighted roadway316 (24.0%)
-15.3%prior 373
Dusk30 (2.3%)
-11.8%prior 34
Dawn14 (1.1%)
-33.3%prior 21
Dark - roadway not lighted12 (0.9%)
-29.4%prior 17
Dark - unknown roadway lighting6 (0.5%)
Other3 (0.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field

Road Surface

Dry1,058 (80.3%)
-5.8%prior 1,123
Wet223 (16.9%)
-15.2%prior 263
Snow15 (1.1%)
36.4%prior 11
Ice9 (0.7%)
50.0%prior 6
Slush8 (0.6%)
60.0%prior 5
Other2 (0.2%)
Sand, mud, dirt, oil, gravel2 (0.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field

Vehicles & Demographics

The top three vehicle makes involved in crashes were Toyota, Honda, and Ford in both years. Toyota's involvement increased from 489 to 518 vehicles, while Honda and Ford saw decreases. Among persons involved, the 26-34 age group remained the largest demographic, increasing slightly from 556 to 573 individuals. Conversely, the 21-25 age group saw a significant decrease in involvement, from 366 persons in 2023 to 281 in 2024.

Top Vehicle Makes (2,669 vehicles)

1
TOYOTA518 (19.4%)
5.9%prior 489
2
HONDA375 (14.1%)
-18.7%prior 461
3
FORD245 (9.2%)
-21.0%prior 310
4
NISSAN170 (6.4%)
-6.1%prior 181
5
CHEVROLET163 (6.1%)
13.2%prior 144
6
SUBARU99 (3.7%)
-11.6%prior 112
7
JEEP97 (3.6%)
-17.1%prior 117
8
HYUNDAI83 (3.1%)
18.6%prior 70
9
MAZDA65 (2.4%)
30.0%prior 50
10
BMW63 (2.4%)
10.5%prior 57

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records

528 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (2,570 persons with recorded sex)

Male1,533 (59.6%)
-3.2%prior 1,584
Female1,037 (40.4%)
-8.5%prior 1,133

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Person-level records linked to crash events

Speed Limit Zones

The 25 mph speed zone was the location for the highest number of crashes in both years, with 912 incidents in 2024 and 954 in 2023. The single fatal crash in each year also occurred within a 25 mph zone. Crashes in 30 mph zones saw a notable decrease, falling from 100 to 56, while incidents in 55 mph zones rose slightly from 107 to 111.

Fatal crashes by zone: 25 mph: 1 of 912 (0.11%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Posted speed limit at crash location

Data Sources & Methodology

Primary Data Source

All crash data in this report is sourced from Massachusetts Crash Data (MassDOT CDV), accessed programmatically via the Arcgis_yearly Open Data API (SODA). This dataset contains official police-reported motor vehicle traffic crash records maintained by the reporting jurisdiction's law enforcement agency. Records are published to the open data portal by the municipality and are subject to the portal's terms of use.

Data Retrieval

  • Access method: Arcgis_yearly Open Data API (SoQL queries)
  • Data format: Structured JSON via REST API
  • Record types queried: Crash events, person records, and vehicle unit records
  • Date filter applied: 2024-01-01 through 2024-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-01-01 through 2024-12-31 (366 days)
  • Geographic scope: MEDFORD, MA
  • Total crash records analyzed: 1,360
  • Total persons involved: 3,119
  • Total vehicles involved: 2,669

Analytical Methodology

  • Severity classification: Uses the KABCO injury scale (K=Fatal, A=Incapacitating injury, B=Non-incapacitating injury, C=Possible injury, O=No injury/property damage only), the standard classification in U.S. Model Minimum Uniform Crash Criteria (MMUCC). Severity is assigned per crash event based on the most severe injury in that crash. A single fatal crash (K) may involve multiple fatalities; therefore the "Persons Killed" count in the headline KPIs may differ from the "Fatal" crash count in the severity breakdown.
  • Contributing factors: Reflect the officer-determined primary contributory cause recorded at the time of the crash report. These are preliminary determinations and may not reflect final investigation findings.
  • Hit-and-run classification: Based on the hit-and-run indicator field in the official crash report, as determined by the responding officer at the scene.
  • Temporal analysis: Day-of-week and hour-of-day distributions are computed from the crash date/time timestamp in each record.
  • Demographics: Age and sex distributions are drawn from person-level records linked to each crash event. A single crash may involve multiple persons.
  • Vehicle data: Make information is drawn from vehicle unit records linked to each crash event.
  • AI commentary: Narrative sections are generated by Google Gemini (large language model) based on the structured data. Commentary is descriptive, not predictive, and should not be interpreted as expert opinion.

Limitations & Disclaimers

  • Only crashes reported to and documented by law enforcement are included. Minor incidents, unreported crashes, and near-misses are not captured in this dataset.
  • Data reflects conditions at the time of the initial police report and may be subject to subsequent corrections, reclassifications, or supplements by the reporting agency.
  • Open data portal records may experience a publication lag - recently occurring crashes may not yet appear in the dataset at the time of report generation.
  • AI-generated commentary is produced by a large language model and is intended to highlight patterns in the data. It does not constitute legal, medical, or professional analysis.
  • Percentages are calculated from reported data and are subject to rounding.

Non-Affiliation Disclosure

This report is produced independently by ThatCarHitMe.com (Injuria.ai). It is not affiliated with, endorsed by, or produced in partnership with any law enforcement agency, municipal government, state department of transportation, or the National Highway Traffic Safety Administration (NHTSA). Data is sourced from publicly available government open data portals.

Data License

The underlying crash data is provided under the municipality's Open Data Terms of Use and is made available to the public for unrestricted use. This analysis and report is © 2026 Injuria.ai and may be cited with attribution using the suggested citation below.

Corrections & Feedback

If you believe any data in this report is inaccurate or have questions about our methodology, please contact: data@injuria.ai. We are committed to accuracy and will issue corrections promptly.

Suggested Citation

ThatCarHitMe.com (Injuria.ai). "MEDFORD, MA Crash Intelligence Report: 2024." Published June 21, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/medford/2024-annual-report

About the Publisher

ThatCarHitMe.com is a crash data intelligence platform developed by Injuria.ai, a legal technology company specializing in traffic safety analytics. We aggregate and analyze publicly available government crash data to produce structured intelligence reports for communities, researchers, journalists, and legal professionals. Our reports combine programmatic data retrieval from official open data portals with AI-assisted narrative analysis.

Questions about this report's data or methodology: data@injuria.ai

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Medford, MA Crash Report — 2024 | ThatCarHitMe.com